The Role of Business English in Higher Education: Enhancing Global Communication and Employability
Bibliographic record
Abstract
This study focuses on the critical role of Business English courses in higher education. It emphasizes their effectiveness in developing students’ communication skills in global and multilingual business settings. Owing to globalization, English has become the dominant language in business and academia. This has made Business English essential for both professional and educational purposes. The study sheds light on the importance of developing and improving business communication skills, including intercultural competence in diverse, multilingual settings, such as writing reports, memos, proposals, and emails. In addition, it suggests effective teaching strategies, including active learning approaches like role-playing, case studies, and group discussions with an integration of digital tools. Accordingly, it focuses on technical language skills and intercultural awareness in the context of global business and recommends curriculum improvements that align with the needs of the industry and foster practical communication skills, teamwork, and lifelong learning. It also suggests that mastering Business English in this way will improve students' academic success and employability in competitive global markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".